Update README.md

README.md

@@ -507,11 +507,11 @@ GPT-NeoX has been used by academic and industry researchers for a variety of hig
 ### Our Research
 EleutherAI and our collaborators have used it in the following publications:
  - Sid Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, McDonell, Jason Phang, Michael Pieler, Prashanth, Shivanshu Purohit, Laria Reynolds, Jon Tow, Ben Wang, and Samuel Weinbach. "[GPT-NeoX-20B: An Open-Source Autoregressive Language Model](https://arxiv.org/abs/2204.06745)." In *Proceedings of the ACL Workshop on Challenges \& Perspectives in Creating Large Language Models* (2022).
- - Stella Biderman, Hailey Schoelkopf, Quentin Gregory Anthony, Herbie Bradley, Kyle O’Brien, Eric Hallahan, Mohammad Aflah Khan et al. "[Pythia: A suite for analyzing large language models across training and scaling](https://arxiv.org/abs/2304.01373)." In _International Conference on Machine Learning_, pp. 2397-2430. PMLR (2023).
+ - Stella Biderman, Hailey Schoelkopf, Quentin Anthony, Herbie Bradley, Kyle O’Brien, Eric Hallahan, Mohammad Aflah Khan et al. "[Pythia: A suite for analyzing large language models across training and scaling](https://arxiv.org/abs/2304.01373)." In _International Conference on Machine Learning_, pp. 2397-2430. PMLR (2023).
  - Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, Edward W. Ayers, Dragomir Radev, and Jeremy Avigad. "[Proofnet: Autoformalizing and formally proving undergraduate-level mathematics](https://arxiv.org/abs/2302.12433). *arXiv preprint arXiv:2302.12433* (2023).
  - Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, Hailey Schoelkopf, Quentin Anthony, Shivanshu Purohit, and Edward Raff. "[Emergent and predictable memorization in large language models.](https://arxiv.org/abs/2304.11158)" *arXiv preprint arXiv:2304.11158* (2023).
  - Hyunwoong Ko, Kichang Yang, Minho Ryu, Taekyoon Choi, Seungmu Yang, and Sungho Park. "[A Technical Report for Polyglot-Ko: Open-Source Large-Scale Korean Language Models](https://arxiv.org/abs/2306.02254)." *arXiv preprint arXiv:2306.02254* (2023).
- - Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats Leon Richter, Quentin Gregory Anthony, Eugene Belilovsky, Irina Rish, and Timothée Lesort. "[Continual Pre-Training of Large Language Models: How to re-warm your model?](https://arxiv.org/abs/2308.04014)" In _Workshop on Efficient Systems for Foundation Models @ ICML_ (2023).
+ - Kshitij Gupta, Benjamin Thérien, Adam Ibrahim, Mats Leon Richter, Quentin Anthony, Eugene Belilovsky, Irina Rish, and Timothée Lesort. "[Continual Pre-Training of Large Language Models: How to re-warm your model?](https://arxiv.org/abs/2308.04014)" In _Workshop on Efficient Systems for Foundation Models @ ICML_ (2023).
 
 ### External Publications
 The following publications by other research groups use this library:
@@ -521,9 +521,12 @@ The following publications by other research groups use this library:
 - Frank F. Xu, Uri Alon, Graham Neubig, and Vincent J. Hellendoorn. "[A Systematic Evaluation of Large Language Models of Code](https://arxiv.org/abs/2202.13169)." In *Proceedings of the ICLR Workshop on Deep Learning For Code* (2022).
 - Eghbal A. Hosseini, Martin A. Schrimpf, Yian Zhang, Samuel Bowman, Noga Zaslavsky, and Evelina Fedorenko. "[Artificial neural network language models align neurally and behaviorally with humans even after a developmentally realistic amount of training.](https://www.biorxiv.org/content/10.1101/2022.10.04.510681)" _BioRxiv_ (2022).
 - Byung-Doh Oh and William Schuler. "[Transformer-Based LM Surprisal Predicts Human Reading Times Best with About Two Billion Training Tokens](https://arxiv.org/abs/2304.11389)." *arXiv preprint arXiv:2304.11389* (2023).
-- Chi, Ta-Chung, Ting-Han Fan, Alexander Rudnicky, and Peter Ramadge. "[Dissecting Transformer Length Extrapolation via the Lens of Receptive Field Analysis](https://aclanthology.org/2023.acl-long.756/)." In _Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)_, pp. 13522-13537 (2023).
+- Ta-Chung Chi, Ting-Han Fan, Alexander Rudnicky, and Peter Ramadge. "[Dissecting Transformer Length Extrapolation via the Lens of Receptive Field Analysis](https://aclanthology.org/2023.acl-long.756/)." In _Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)_, pp. 13522-13537 (2023).
 - Xidong Feng, Yicheng Luo, Ziyan Wang, Hongrui Tang, Mengyue Yang, Kun Shao, David Mguni, Yali Du, and Jun Wang. "[ChessGPT: Bridging Policy Learning and Language Modeling.](https://arxiv.org/abs/2306.09200)" _arXiv preprint arXiv:2306.09200_ (2023).
-- Dollar, Orion Walker, Sameera Horawalavithana, Scott Vasquez, W. James Pfaendtner, and Svitlana Volkova. "[MolJET: Multimodal Joint Embedding Transformer for Conditional de novo Molecular Design and Multi-Property Optimization.](https://openreview.net/pdf?id=7UudBVsIrr)" _preprint_ (2022).
+- Orion Walker Dollar, Sameera Horawalavithana, Scott Vasquez, W. James Pfaendtner, and Svitlana Volkova. "[MolJET: Multimodal Joint Embedding Transformer for Conditional de novo Molecular Design and Multi-Property Optimization.](https://openreview.net/pdf?id=7UudBVsIrr)" _preprint_ (2023).
+- Jean Kaddour and Qi Liu. "[Text Data Augmentation in Low-Resource Settings via Fine-Tuning of Large Language Models](https://arxiv.org/abs/2310.01119)." _arXiv:2310.01119_ (2023).
+- Alon Albalak, Liangming Pan, Colin Raffel, and William Yang Wang. "[Efficient Online Data Mixing For Language Model Pre-Training](https://alon-albalak.github.io/images/Online_Data_Mixing.pdf)." _preprint_ (2023).
+- Eghbal A. Hosseini and Evelina Fedorenko. "[Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language](https://www.biorxiv.org/content/10.1101/2023.11.05.564832v1)." _bioRxiv_ (2023).
 
 ### Models
 The following models were trained using this library:
@@ -540,6 +543,7 @@ The following models were trained using this library:
 - [EleutherAI](https://eleuther.ai/)'s [Polyglot-Ko (1.3B through 12.8B)](https://github.com/EleutherAI/polyglot) (Korean)
 - [Korea University](http://nlp.korea.ac.kr/)'s [KULLM-Polyglot (5.8B and 12.8B)](https://github.com/nlpai-lab/KULLM) (Korean)
 - [LearnItAnyway](https://huggingface.co/LearnItAnyway)'s [LLaVA-Polyglot-Ko (1.3B)](https://huggingface.co/LearnItAnyway/llava-polyglot-ko-1.3b-hf) (Korean)
+- [Rinna Co.](https://rinna.co.jp/)'s [japanese-gpt-neox-3.6b](https://huggingface.co/rinna/japanese-gpt-neox-3.6b) (Japanese)
 - [Rinna Co.](https://rinna.co.jp/)'s [bilingual-gpt-neox-4b](https://huggingface.co/rinna/bilingual-gpt-neox-4b) (English / Japanese)
 - [CyberAgent](https://www.cyberagent.co.jp/en/)'s [Open-CLM (125M through 7B)](https://huggingface.co/cyberagent/open-calm-7b) (Japanese)
 - [The Hungarian Research Centre for Linguistics](https://nytud.hu/en)'s [PULI GPTrio (6.7B)](https://huggingface.co/NYTK/PULI-GPTrio) (Hungarian / English / Chinese)
@@ -548,13 +552,14 @@ The following models were trained using this library:
 
 **Code Models**
 - [Carnegie Mellon University](https://www.cmu.edu/)'s [PolyCoder (160M through 2.7B)](https://github.com/VHellendoorn/Code-LMs)
-- [StabilityAI](https://stability.ai/)'s Code [StableCode (1.3B)](https://stability.ai/blog/stablecode-llm-generative-ai-coding)
+- [StabilityAI](https://stability.ai/)'s [StableCode (1.3B)](https://stability.ai/blog/stablecode-llm-generative-ai-coding)
+- StabilityAI's [StableCode-Completion-Alpha (3B)](https://stability.ai/blog/stablecode-llm-generative-ai-coding)
+ StableCode-Completion-Alpha-3B-4k
 
 **Other Modalities**
 -  [University College London](https://www.ucl.ac.uk/computer-science/)'s [ChessGPT-3B](https://huggingface.co/Waterhorse/chessgpt-base-v1)
 -  [Gretel](https://gretel.ai/)'s [Text-to-Table](https://huggingface.co/gretelai/text2table)
 
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 ## Licensing
 
 This repository hosts code that is part of EleutherAI's GPT-NeoX project. Copyright (c) 2021, EleutherAI. Licensed under the Apache License: